In this study, the authors present a stable and reliable route selection technique based on the nodes’ mobility in mobile ad hoc networks. Here, a path is chosen for data routing that depends on some points that are computed based on a node's speed, direction and pause time. A trust module generates a threshold value to compare these points, which are known as the mobility_factor of a mobile node. Mobility_factor is used for selecting nodes to establish a path between source and destination nodes. They have carried out simulations of dynamic source routing (DSR) and ad hoc on-demand distance vector (AODV) routing protocols using random Waypoint and Levy Walk mobility models with and without their proposed technique. Through simulation results we have shown that when used with our proposed mobility aware route selection technique, both of the protocols perform much better than the basic AODV and DSR. Also, the proposed protocols outperform the existing routing protocols, mobility aware routing protocol as well as mobility and load routing.

Ubiquitous sensing and unique characteristics of wireless sensor networks (WSNs) have led to an increase in application areas such as smart parking, environmental monitoring, automotive industries and sports. In recent years, WSNs have gained more significance as the foundation infrastructure for the Internet of Things (IoT), which has greatly increased the number of connected objects with instantaneous communication and data processing. However, designing energy-efficient models for integrating WSNs into IoT is a challenging issue due to scalability and interoperability of IoT, and previous approaches designed for WSNs cannot be applied directly. This study proposes two energy-efficient models for WSNs in the IoT environment: (i) a service-aware clustering model where individual sensor nodes are assigned roles based on their service delivery; and (ii) an energy-aware clustering model. Performance evaluation shows better energy efficiency, end-to-end delay and network load balance of the proposed models for integrating wireless sensor networks into the IoT protocol compared with low-energy adaptive clustering hierarchy centralised protocol and fuzzy C-means clustering protocol.

Sensor nodes once deployed onto the field are mostly provided with little or no attention making them prone to physical attacks by adversaries. Various security frameworks have been proposed to mitigate tampering; others also ensure authentication of sensor nodes. Energy is a limited resource and as such, the need to develop energy efficient frameworks that ensure authentication and thwart tampering of deployed sensor nodes. In this study, a framework comprising an authentication algorithm with a hardware-based tamper detection and recovery procedure is proposed. An interrupt-driven tamper detection and recovery mechanism is employed to aid the isolation of compromised nodes. MD-5, SHA-1, SHA-224, SHA-256, SHA-384 and SHA-512 hash functions were reviewed and simulation done to select the most energy-efficient option (SHA-224) for use with the authentication algorithm. The proposed framework was compared with other existing authentication frameworks in the area of energy efficiency. The result show that the proposed framework is the most energy-efficient. The proposed framework, TinySec, SenSec and MiniSec were analysed against node subversion and false node attacks; the proposed framework can detect compromised nodes in all two attacks but the rest were only potent against false nodes and not against node subversion.